Jupyter : Security Vulnerabilities, CVEs,

OAuthenticator provides plugins for JupyterHub to use common OAuth providers, as well as base classes for writing one's own Authenticators with any OAuth 2.0 provider. `GoogleOAuthenticator.hosted_domain` is used to restrict what Google accounts can be authorized access to a JupyterHub. The restriction is intented to be to Google accounts part of one or more Google organization verified to control specified domain(s). Prior to version 16.3.0, the actual restriction has been to Google accounts with emails ending with the domain. Such accounts could have been created by anyone which at one time was able to read an email associated with the domain. This was described by Dylan Ayrey (@dxa4481) in this [blog post] from 15th December 2023). OAuthenticator 16.3.0 contains a patch for this issue. As a workaround, restrict who can login another way, such as `allowed_users` or `allowed_google_groups`.

JupyterHub is an open source multi-user server for Jupyter notebooks. By tricking a user into visiting a malicious subdomain, the attacker can achieve an XSS directly affecting the former's session. More precisely, in the context of JupyterHub, this XSS could achieve full access to JupyterHub API and user's single-user server. The affected configurations are single-origin JupyterHub deployments and JupyterHub deployments with user-controlled applications running on subdomains or peer subdomains of either the Hub or a single-user server. This vulnerability is fixed in 4.1.0.

Jupyter Server Proxy allows users to run arbitrary external processes alongside their Jupyter notebook servers and provides authenticated web access. Prior to versions 3.2.3 and 4.1.1, Jupyter Server Proxy did not check user authentication appropriately when proxying websockets, allowing unauthenticated access to anyone who had network access to the Jupyter server endpoint. This vulnerability can allow unauthenticated remote access to any websocket endpoint set up to be accessible via Jupyter Server Proxy. In many cases, this leads to remote unauthenticated arbitrary code execution, due to how affected instances use websockets. The websocket endpoints exposed by `jupyter_server` itself is not affected. Projects that do not rely on websockets are also not affected. Versions 3.2.3 and 4.1.1 contain a fix for this issue.

JupyterLab is an extensible environment for interactive and reproducible computing, based on the Jupyter Notebook and Architecture. Users of JupyterLab who click on a malicious link may get their `Authorization` and `XSRFToken` tokens exposed to a third party when running an older `jupyter-server` version. JupyterLab versions 4.1.0b2, 4.0.11, and 3.6.7 are patched. No workaround has been identified, however users should ensure to upgrade `jupyter-server` to version 2.7.2 or newer which includes a redirect vulnerability fix.

JupyterLab is an extensible environment for interactive and reproducible computing, based on the Jupyter Notebook and Architecture. This vulnerability depends on user interaction by opening a malicious Markdown file using JupyterLab preview feature. A malicious user can access any data that the attacked user has access to as well as perform arbitrary requests acting as the attacked user. JupyterLab version 4.0.11 has been patched. Users are advised to upgrade. Users unable to upgrade should disable the table of contents extension.

jupyter-lsp is a coding assistance tool for JupyterLab (code navigation + hover suggestions + linters + autocompletion + rename) using Language Server Protocol. Installations of jupyter-lsp running in environments without configured file system access control (on the operating system level), and with jupyter-server instances exposed to non-trusted network are vulnerable to unauthorised access and modification of file system beyond the jupyter root directory. This issue has been patched in version 2.2.2 and all users are advised to upgrade. Users unable to upgrade should uninstall jupyter-lsp.

The Jupyter Server provides the backend (i.e. the core services, APIs, and REST endpoints) for Jupyter web applications like Jupyter notebook, JupyterLab, and Voila. Unhandled errors in API requests coming from an authenticated user include traceback information, which can include path information. There is no known mechanism by which to trigger these errors without authentication, so the paths revealed are not considered particularly sensitive, given that the requesting user has arbitrary execution permissions already in the same environment. A fix has been introduced in commit `0056c3aa52` which no longer includes traceback information in JSON error responses. For compatibility, the traceback field is present, but always empty. This commit has been included in version 2.11.2. Users are advised to upgrade. There are no known workarounds for this vulnerability.

dockerspawner is a tool to spawn JupyterHub single user servers in Docker containers. Users of JupyterHub deployments running DockerSpawner starting with 0.11.0 without specifying `DockerSpawner.allowed_images` configuration allow users to launch _any_ pullable docker image, instead of restricting to only the single configured image, as intended. This issue has been addressed in commit `3ba4b665b` which has been included in dockerspawner release version 13. Users are advised to upgrade. Users unable to upgrade should explicitly set `DockerSpawner.allowed_images` to a non-empty list containing only the default image will result in the intended default behavior.

jupyter-server is the backend for Jupyter web applications. Improper cross-site credential checks on `/files/` URLs could allow exposure of certain file contents, or accessing files when opening untrusted files via "Open image in new tab". This issue has been addressed in commit `87a49272728` which has been included in release `2.7.2`. Users are advised to upgrade. Users unable to upgrade may use the lower performance `--ContentsManager.files_handler_class=jupyter_server.files.handlers.FilesHandler`, which implements the correct checks.

jupyter-server is the backend for Jupyter web applications. Open Redirect Vulnerability. Maliciously crafted login links to known Jupyter Servers can cause successful login or an already logged-in session to be redirected to arbitrary sites, which should be restricted to Jupyter Server-served URLs. This issue has been addressed in commit `29036259` which is included in release 2.7.2. Users are advised to upgrade. There are no known workarounds for this vulnerability.

Jupyter Core is a package for the core common functionality of Jupyter projects. Jupyter Core prior to version 4.11.2 contains an arbitrary code execution vulnerability in `jupyter_core` that stems from `jupyter_core` executing untrusted files in CWD. This vulnerability allows one user to run code as another. Version 4.11.2 contains a patch for this issue. There are no known workarounds.

OAuthenticator is an OAuth token library for the JupyerHub login handler. CILogonOAuthenticator is provided by the OAuthenticator package, and lets users log in to a JupyterHub via CILogon. This is primarily used to restrict a JupyterHub only to users of a given institute. The allowed_idps configuration trait of CILogonOAuthenticator is documented to be a list of domains that indicate the institutions whose users are authorized to access this JupyterHub. This authorization is validated by ensuring that the *email* field provided to us by CILogon has a *domain* that matches one of the domains listed in `allowed_idps`.If `allowed_idps` contains `berkeley.edu`, you might expect only users with valid current credentials provided by University of California, Berkeley to be able to access the JupyterHub. However, CILogonOAuthenticator does *not* verify which provider is used by the user to login, only the email address provided. So a user can login with a GitHub account that has email set to `<something>@berkeley.edu`, and that will be treated exactly the same as someone logging in using the UC Berkeley official Identity Provider. The patch fixing this issue makes a *breaking change* in how `allowed_idps` is interpreted. It's no longer a list of domains, but configuration representing the `EntityID` of the IdPs that are allowed, picked from the [list maintained by CILogon](https://cilogon.org/idplist/). Users are advised to upgrade.

Jupyter Server provides the backend (i.e. the core services, APIs, and REST endpoints) for Jupyter web applications like Jupyter Notebook. Prior to version 1.17.1, if notebook server is started with a value of `root_dir` that contains the starting user's home directory, then the underlying REST API can be used to leak the access token assigned at start time by guessing/brute forcing the PID of the jupyter server. While this requires an authenticated user session, this URL can be used from a cross-site scripting payload or from a hooked or otherwise compromised browser to leak this access token to a malicious third party. This token can be used along with the REST API to interact with Jupyter services/notebooks such as modifying or overwriting critical files, such as .bashrc or .ssh/authorized_keys, allowing a malicious user to read potentially sensitive data and possibly gain control of the impacted system. This issue is patched in version 1.17.1.

Jupyter Notebook is a web-based notebook environment for interactive computing. Prior to version 6.4.12, authenticated requests to the notebook server with `ContentsManager.allow_hidden = False` only prevented listing the contents of hidden directories, not accessing individual hidden files or files in hidden directories (i.e. hidden files were 'hidden' but not 'inaccessible'). This could lead to notebook configurations allowing authenticated access to files that may reasonably be expected to be disallowed. Because fully authenticated requests are required, this is of relatively low impact. But if a server's root directory contains sensitive files whose only protection from the server is being hidden (e.g. `~/.ssh` while serving $HOME), then any authenticated requests could access files if their names are guessable. Such contexts also necessarily have full access to the server and therefore execution permissions, which also generally grants access to all the same files. So this does not generally result in any privilege escalation or increase in information access, only an additional, unintended means by which the files could be accessed. Version 6.4.12 contains a patch for this issue. There are currently no known workarounds.

The Jupyter notebook is a web-based notebook environment for interactive computing. Prior to version 6.4.9, unauthorized actors can access sensitive information from server logs. Anytime a 5xx error is triggered, the auth cookie and other header values are recorded in Jupyter server logs by default. Considering these logs do not require root access, an attacker can monitor these logs, steal sensitive auth/cookie information, and gain access to the Jupyter server. Jupyter notebook version 6.4.x contains a patch for this issue. There are currently no known workarounds.

The Jupyter Server provides the backend (i.e. the core services, APIs, and REST endpoints) for Jupyter web applications. Prior to version 1.15.4, unauthorized actors can access sensitive information from server logs. Anytime a 5xx error is triggered, the auth cookie and other header values are recorded in Jupyter Server logs by default. Considering these logs do not require root access, an attacker can monitor these logs, steal sensitive auth/cookie information, and gain access to the Jupyter server. Jupyter Server version 1.15.4 contains a patch for this issue. There are currently no known workarounds.

Jupyter Server Proxy is a Jupyter notebook server extension to proxy web services. Versions of Jupyter Server Proxy prior to 3.2.1 are vulnerable to Server-Side Request Forgery (SSRF). Any user deploying Jupyter Server or Notebook with jupyter-proxy-server extension enabled is affected. A lack of input validation allows authenticated clients to proxy requests to other hosts, bypassing the `allowed_hosts` check. Because authentication is required, which already grants permissions to make the same requests via kernel or terminal execution, this is considered low to moderate severity. Users may upgrade to version 3.2.1 to receive a patch or, as a workaround, install the patch manually.

JupyterHub is an open source multi-user server for Jupyter notebooks. In affected versions users who have multiple JupyterLab tabs open in the same browser session, may see incomplete logout from the single-user server, as fresh credentials (for the single-user server only, not the Hub) reinstated after logout, if another active JupyterLab session is open while the logout takes place. Upgrade to JupyterHub 1.5. For distributed deployments, it is jupyterhub in the _user_ environment that needs patching. There are no patches necessary in the Hub environment. The only workaround is to make sure that only one JupyterLab tab is open when you log out.

nbdime provides tools for diffing and merging of Jupyter Notebooks. In affected versions a stored cross-site scripting (XSS) issue exists within the Jupyter-owned nbdime project. It appears that when reading the file name and path from disk, the extension does not sanitize the string it constructs before returning it to be displayed. The diffNotebookCheckpoint function within nbdime causes this issue. When attempting to display the name of the local notebook (diffNotebookCheckpoint), nbdime appears to simply append .ipynb to the name of the input file. The NbdimeWidget is then created, and the base string is passed through to the request API function. From there, the frontend simply renders the HTML tag and anything along with it. Users are advised to patch to the most recent version of the affected product.

BinderHub is a kubernetes-based cloud service that allows users to share reproducible interactive computing environments from code repositories. In affected versions a remote code execution vulnerability has been identified in BinderHub, where providing BinderHub with maliciously crafted input could execute code in the BinderHub context, with the potential to egress credentials of the BinderHub deployment, including JupyterHub API tokens, kubernetes service accounts, and docker registry credentials. This may provide the ability to manipulate images and other user created pods in the deployment, with the potential to escalate to the host depending on the underlying kubernetes configuration. Users are advised to update to version 0.2.0-n653. If users are unable to update they may disable the git repo provider by specifying the `BinderHub.repo_providers` as a workaround.

The GitHub Security Lab discovered sixteen ways to exploit a cross-site scripting vulnerability in nbconvert. When using nbconvert to generate an HTML version of a user-controllable notebook, it is possible to inject arbitrary HTML which may lead to cross-site scripting (XSS) vulnerabilities if these HTML notebooks are served by a web server (eg: nbviewer).

The Jupyter notebook is a web-based notebook environment for interactive computing. In affected versions untrusted notebook can execute code on load. Jupyter Notebook uses a deprecated version of Google Caja to sanitize user inputs. A public Caja bypass can be used to trigger an XSS when a victim opens a malicious ipynb document in Jupyter Notebook. The XSS allows an attacker to execute arbitrary code on the victim computer using Jupyter APIs.

JupyterLab is a user interface for Project Jupyter which will eventually replace the classic Jupyter Notebook. In affected versions untrusted notebook can execute code on load. In particular JupyterLab doesn’t sanitize the action attribute of html `<form>`. Using this it is possible to trigger the form validation outside of the form itself. This is a remote code execution, but requires user action to open a notebook.

JupyterHub 1.1.0 allows CSRF in the admin panel via a request that lacks an _xsrf field, as demonstrated by a /hub/api/user request (to add or remove a user account).

The Jupyter Server provides the backend (i.e. the core services, APIs, and REST endpoints) for Jupyter web applications like Jupyter notebook, JupyterLab, and Voila. In Jupyter Server before version 1.1.1, an open redirect vulnerability could cause the jupyter server to redirect the browser to a different malicious website. All jupyter servers running without a base_url prefix are technically affected, however, these maliciously crafted links can only be reasonably made for known jupyter server hosts. A link to your jupyter server may *appear* safe, but ultimately redirect to a spoofed server on the public internet. This same vulnerability was patched in upstream notebook v5.7.8. This is fixed in jupyter_server 1.1.1. If upgrade is not available, a workaround can be to run your server on a url prefix: "jupyter server --ServerApp.base_url=/jupyter/".